Sounds as an auditory percept are little understood in terms of their potential to play a significant role for research and creative projects particularly involving high-dimensional systems. The applications of sound in interface design include voice recognition, teleconferencing, audio archiving, sound localization, audio alarms, audio cues, carcons, and data sonifications. Many of these applications serve the purpose of enhancing visualization or compensating for visual overload. For example, audio cues are sounds for location identification guiding visual search for a point of interest. Among these applications data sonification comes close to utilizing auditory percepts for enhancing an understanding of data.
To bring auditory percepts into research projects involves (1) designing sounds for an optimal representation of systems' behaviors, and (2) incorporating sounds in interactivity. For exploring systems, observers often encounter cumbersome tasks such as entering control data by typing or creating input files. Output data are also observed often in the form of numbers or graphic representations. When exploring high-dimensional systems a need exists for alternative ways of interacting with the systems. An efficient method for entering control data with real-time observation of the consequences are keys to an intuitive exploration. The use of sounds has been observed to offer efficient and perceptive learning in massive parameter space. As a system output, sound functions as an auditory feedback, linking full circle in an exploration process for observers to monitor their own interaction as well as the behavioral changes of systems under study.
The unique characteristics of sound lie in the omnidirectional characteristic of acoustic signals. This characteristic can be understood in two ways. First, the obvious meaning of "omnidirectional" refers to the way sounds propagate in space. This accounts for the physics of sounds such as diffusion, reflection, and diffraction as well as our perceptual ability to process the spatial distribution of sounds. Secondly, the term "omnidirectional" can be understood from a compositional point of view focusing on acoustic materials or elements, their pitch and rhythmic relationships, their sizes in units and groups. In other words, we can also apply "omnidirectional" to refer to classes of sounds within a material differentiation space. By listening to the way classes of materials are derived from an original set and developed through or without transitional states, one achieves a dynamical observation. An example can be found where the acoustic material differentiation is based upon the content area of an "information space."
The prior art lacks the advantage of a system and method for representing the omnidimensional sound characteristics in a comprehensible manner. Such a system and method would translate multi-dimensional sound representations or "manifolds" into two or three dimensions that can be understood and manipulated more readily by the observer. A "manifold interface" provides such a translation or mapping, which can further be applied to other multi-dimensional control systems in addition to sound signal generation and sound analysis. The benefit of this mapping is that humans understand movement in 2D and 3D, whereas it may be difficult to intuitively grasp high-dimensional spaces. The manifold interface technology translates movements performed in the intuitive space into movements in a space that is otherwise difficult to grasp intuitively.